{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<p align=\"center\">\n",
    "    <img src=\"https://github.com/GeostatsGuy/GeostatsPy/blob/master/TCG_color_logo.png?raw=true\" width=\"220\" height=\"240\" />\n",
    "\n",
    "</p>\n",
    "\n",
    "## Subsurface Data Analytics \n",
    "\n",
    "## K-means Clustering\n",
    "\n",
    "\n",
    "### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "\n",
    "#### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n",
    "\n",
    "### PGE 383 Exercise: K-means Clustering for Subsurface Data Analytics in Python \n",
    "\n",
    "Here's a simple workflow, demonstration of K-means clustering for subsurface modeling workflows. This should help you get started with inferential methods to find patterns in your subsurface data sets.  \n",
    "\n",
    "This workflow is broken up to the primary steps of:\n",
    "\n",
    "* assign initial random prototype with labels\n",
    "\n",
    "* assign samples to the nearest prototype label\n",
    "\n",
    "* update prototype based on centroids of samples belonging to this prototype\n",
    "\n",
    "* iterate until no sample assignments change\n",
    "\n",
    "This allows us to be able to watch the method in action, as opposed to just getting a result.  I think this is more instructive.\n",
    "\n",
    "For this workflow I have modified code from the tutorial provided by Ben Keen as functions to take care of the steps (assign training data to the nearest prototype, update the prototype to the centroid of the assigned data).  The original tutorial is avaiable at [here](http://benalexkeen.com/k-means-clustering-in-python). All I did was specify the method to my data example for clarity, and include the normalized and original data. Appreciation to Ben!\n",
    "\n",
    "#### k-Means Clustering\n",
    "\n",
    "The K-means clustering approach is primaryly applied as an unsupervised method for classification:\n",
    "\n",
    "* **Prototype Method** - represents the training data with number of synthetic cases in the features space. For K-means clustering we assign and iteratively update $K$ prototypes.\n",
    "\n",
    "* **Iterative Solution** - the initial prototypes are assigned randomly in the feature space, the labels for each training sample are updated to the nearest prototype, then the prototypes are adjusted to the centroid of their assigned training data, repeat until there is no further update to the training data assignments.\n",
    "\n",
    "* **Unsupervised Learning** - the training data are not labeled and are assigned $K$ labels based on their proximity to the prototypes in the feature space.  The idea is that similar things, proximity in feature space, should belong to the same category.  \n",
    "\n",
    "* **Feature Weighting** - the procedure depends on the 'distance' between training samples and prototypes in feature space.  Distance is treated as the 'inverse' of similarity. If the features have significantly different magnitudes, the feature(s) with the largest magnitudes and ranges will dominate the process.  One approach is to sandardize / normalize the variables.  Also, by-feature weighting may be applied.  In this demonstration we normalize the features to range from 0.0 to 1.0.\n",
    "\n",
    "* Supervised Learning Variant for Classification of the Feature Space - applies multiple prototypes in each category to then constructs a decision boundary based on nearest prototype.  More prototypes per category results in a more complicated decision boundary in the feature space.  \n",
    "\n",
    "#### Objective \n",
    "\n",
    "In the PGE 383: Subsurface Machine Learning class I want to provide hands-on experience with building subsurface modeling workflows. Python provides an excellent vehicle to accomplish this. I have coded a package called GeostatsPy with GSLIB: Geostatistical Library (Deutsch and Journel, 1998) functionality that provides basic building blocks for building subsurface modeling workflows. \n",
    "\n",
    "The objective is to remove the hurdles of subsurface modeling workflow construction by providing building blocks and sufficient examples. This is not a coding class per se, but we need the ability to 'script' workflows working with numerical methods.    \n",
    "\n",
    "#### Getting Started\n",
    "\n",
    "Here's the steps to get setup in Python with the GeostatsPy package:\n",
    "\n",
    "1. Install Anaconda 3 on your machine (https://www.anaconda.com/download/). \n",
    "2. From Anaconda Navigator (within Anaconda3 group), go to the environment tab, click on base (root) green arrow and open a terminal. \n",
    "3. In the terminal type: pip install geostatspy. \n",
    "4. Open Jupyter and in the top block get started by copy and pasting the code block below from this Jupyter Notebook to start using the geostatspy functionality. \n",
    "\n",
    "You will need to copy the data file to your working directory.  They are available here:\n",
    "\n",
    "* Tabular data - unconv_MV.csv at https://git.io/fjmBH.\n",
    "\n",
    "There are exampled below with these functions. You can go here to see a list of the available functions, https://git.io/fh4eX, other example workflows and source code. \n",
    "\n",
    "#### Install Packages\n",
    "\n",
    "We will include the standard packages for DataFrames and ndarrays and add sci-kit-learn (sklearn) for machine learning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geostatspy.GSLIB as GSLIB          # GSLIB utilies, visualization and wrapper\n",
    "import geostatspy.geostats as geostats    # GSLIB methods convert to Python        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will also need some standard packages. These should have been installed with Anaconda 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np                        # ndarrys for gridded data\n",
    "import pandas as pd                       # DataFrames for tabular data\n",
    "import os                                 # set working directory, run executables\n",
    "import matplotlib.pyplot as plt           # for plotting\n",
    "import copy                               # for deep copies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Declare Functions\n",
    "\n",
    "The following functions perform the steps required by K-means clustering.\n",
    "\n",
    "* assign the training data to the nearest prototype\n",
    "\n",
    "* update the prototype to the centroid of the assigned training data\n",
    "\n",
    "Don't be concerned if you don't understand the code, we have used some advanced approaches for the benefit of concise code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Assignment function to assigned training data to the nearest prototype (code modified from Ben Keen, http://benalexkeen.com/k-means-clustering-in-python/)\n",
    "def assignment(df, centroids):\n",
    "    for i in centroids.keys():\n",
    "        df['distance_from_{}'.format(i)] = (    # use the normalized features and centroids\n",
    "            np.sqrt(\n",
    "                (df['Norm_Porosity'] - centroids[i][2]) ** 2\n",
    "                + (df['Norm_AI'] - centroids[i][3]) ** 2\n",
    "            )\n",
    "        )\n",
    "    centroid_distance_cols = ['distance_from_{}'.format(i) for i in centroids.keys()]\n",
    "    df['closest'] = df.loc[:, centroid_distance_cols].idxmin(axis=1)\n",
    "    df['closest'] = df['closest'].map(lambda x: int(x.lstrip('distance_from_')))\n",
    "    df['color'] = df['closest'].map(lambda x: colmap[x])\n",
    "    return df\n",
    "\n",
    "# Update function to shift the prototype to the centroid of the training data assigned to the prototype (code modified from Ben Keen, http://benalexkeen.com/k-means-clustering-in-python/)\n",
    "def update(k,pormin,pormax,AImin,AImax):\n",
    "    for i in centroids.keys():\n",
    "        centroids[i][2] = np.mean(df[df['closest'] == i]['Norm_Porosity'])\n",
    "        centroids[i][3] = np.mean(df[df['closest'] == i]['Norm_AI'])\n",
    "        centroids[i][0] = centroids[i][2] * (pormax-pormin) + pormin\n",
    "        centroids[i][1] = centroids[i][3] * (AImax-AImin) + AImin\n",
    "    return k"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Set the working directory\n",
    "\n",
    "I always like to do this so I don't lose files and to simplify subsequent read and writes (avoid including the full address each time). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"C:/PGE383\")                     # set the working directory with the input data file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Loading Data\n",
    "Let's load the provided multivariate, spatial dataset '12_sample_data.csv'.  It is a comma delimited file with: \n",
    "\n",
    "* X and Y coordinates ($m$)\n",
    "* facies 0 and 1 \n",
    "* porosity (fraction)\n",
    "* permeability ($mD$)\n",
    "* acoustic impedance ($\\frac{kg}{m^3} \\cdot \\frac{m}{s} \\cdot 10^3$). \n",
    "\n",
    "We load it with the pandas 'read_csv' function into a data frame we called 'df' and then preview it to make sure it loaded correctly.\n",
    "\n",
    "**Python Tip: using functions from a package** just type the label for the package that we declared at the beginning:\n",
    "\n",
    "```python\n",
    "import pandas as pd\n",
    "```\n",
    "\n",
    "so we can access the pandas function 'read_csv' with the command: \n",
    "\n",
    "```python\n",
    "pd.read_csv()\n",
    "```\n",
    "\n",
    "but read csv has required input parameters. The essential one is the name of the file. For our circumstance all the other default parameters are fine. If you want to see all the possible parameters for this function, just go to the docs [here](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html).  \n",
    "\n",
    "* The docs are always helpful\n",
    "* There is often a lot of flexibility for Python functions, possible through using various inputs parameters\n",
    "\n",
    "also, the program has an output, a pandas DataFrame loaded from the data.  So we have to specficy the name / variable representing that new object.\n",
    "\n",
    "```python\n",
    "df = pd.read_csv(\"12_sample_data.csv\")  \n",
    "```\n",
    "\n",
    "Let's run this command to load the data and then this command to extract a random subset of the data.\n",
    "\n",
    "```python\n",
    "df = df.sample(frac=.30, random_state = 73073); \n",
    "df = df.reset_index()\n",
    "```\n",
    "\n",
    "We do this to reduce the number of data for ease of visualization (hard to see if too many points on our plots)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('12_sample_data.csv')    # load our data table\n",
    "df = df.sample(frac=.30, random_state = 73073); df = df.reset_index() # extract 30% random to reduce the number of data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Summary Statistics for Tabular Data\n",
    "\n",
    "The table includes porosity (fraction) and acoustic impedance ($\\frac{kg}{m^3} \\cdot \\frac{m}{s} \\cdot 10^3$) that we will work with in the demonstration below.\n",
    "\n",
    "There are a lot of efficient methods to calculate summary statistics from tabular data in DataFrames. The describe command provides count, mean, minimum, maximum, and quartiles all in a nice data table. We use transpose just to flip the table so that features are on the rows and the statistics are on the columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th>std</th>\n",
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       "      <th>max</th>\n",
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       "      <td>261.048611</td>\n",
       "      <td>136.830267</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>144.750000</td>\n",
       "      <td>270.000000</td>\n",
       "      <td>381.250000</td>\n",
       "      <td>478.000000</td>\n",
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       "      <th>X</th>\n",
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       "      <td>449.375000</td>\n",
       "      <td>263.691435</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>242.500000</td>\n",
       "      <td>400.000000</td>\n",
       "      <td>650.000000</td>\n",
       "      <td>980.000000</td>\n",
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       "      <td>144.0</td>\n",
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       "      <td>289.228936</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>300.000000</td>\n",
       "      <td>579.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>979.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Facies</th>\n",
       "      <td>144.0</td>\n",
       "      <td>0.659722</td>\n",
       "      <td>0.475456</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porosity</th>\n",
       "      <td>144.0</td>\n",
       "      <td>0.190700</td>\n",
       "      <td>0.031972</td>\n",
       "      <td>0.131230</td>\n",
       "      <td>0.166621</td>\n",
       "      <td>0.188733</td>\n",
       "      <td>0.217234</td>\n",
       "      <td>0.256172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Perm</th>\n",
       "      <td>144.0</td>\n",
       "      <td>510.036736</td>\n",
       "      <td>1136.459068</td>\n",
       "      <td>0.039555</td>\n",
       "      <td>6.950509</td>\n",
       "      <td>56.886770</td>\n",
       "      <td>356.658709</td>\n",
       "      <td>7452.343369</td>\n",
       "    </tr>\n",
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       "      <th>AI</th>\n",
       "      <td>144.0</td>\n",
       "      <td>3746.825725</td>\n",
       "      <td>793.196589</td>\n",
       "      <td>1961.600397</td>\n",
       "      <td>3167.631744</td>\n",
       "      <td>3668.526774</td>\n",
       "      <td>4244.264532</td>\n",
       "      <td>6194.573653</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "          count         mean          std          min          25%  \\\n",
       "index     144.0   261.048611   136.830267     1.000000   144.750000   \n",
       "X         144.0   449.375000   263.691435     0.000000   242.500000   \n",
       "Y         144.0   542.979167   289.228936    19.000000   300.000000   \n",
       "Facies    144.0     0.659722     0.475456     0.000000     0.000000   \n",
       "Porosity  144.0     0.190700     0.031972     0.131230     0.166621   \n",
       "Perm      144.0   510.036736  1136.459068     0.039555     6.950509   \n",
       "AI        144.0  3746.825725   793.196589  1961.600397  3167.631744   \n",
       "\n",
       "                  50%          75%          max  \n",
       "index      270.000000   381.250000   478.000000  \n",
       "X          400.000000   650.000000   980.000000  \n",
       "Y          579.000000   800.000000   979.000000  \n",
       "Facies       1.000000     1.000000     1.000000  \n",
       "Porosity     0.188733     0.217234     0.256172  \n",
       "Perm        56.886770   356.658709  7452.343369  \n",
       "AI        3668.526774  4244.264532  6194.573653  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The two features are quite incompatible.  They have dramatically different:\n",
    "\n",
    "* magnitudes / averages\n",
    "\n",
    "* variances / ranges\n",
    "\n",
    "We should make a normalized version of each.  We will scale the variables to range from 0 to 1.  \n",
    "\n",
    "* There is no distribution shape change.\n",
    "\n",
    "We will use these normalized values for calculating distance in our workflow:\n",
    "\n",
    "* to remove the influence of magnitude and range on our similarity calculation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "pormin = df['Porosity'].min(); pormax = df['Porosity'].max()\n",
    "AImin = df['AI'].min(); AImax = df['AI'].max()\n",
    "\n",
    "df['Norm_Porosity'] = (df['Porosity']-pormin)/(pormax - pormin)\n",
    "df['Norm_AI'] = (df['AI']-AImin)/(AImax - AImin)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's confirm that our normalized porosity and acoustic impedance now range between 0 and 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.000000</td>\n",
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       "      <td>0.190700</td>\n",
       "      <td>0.031972</td>\n",
       "      <td>0.131230</td>\n",
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       "      <td>0.217234</td>\n",
       "      <td>0.256172</td>\n",
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       "      <td>3167.631744</td>\n",
       "      <td>3668.526774</td>\n",
       "      <td>4244.264532</td>\n",
       "      <td>6194.573653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norm_Porosity</th>\n",
       "      <td>144.0</td>\n",
       "      <td>0.475986</td>\n",
       "      <td>0.255894</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.283258</td>\n",
       "      <td>0.460240</td>\n",
       "      <td>0.688350</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Norm_AI</th>\n",
       "      <td>144.0</td>\n",
       "      <td>0.421743</td>\n",
       "      <td>0.187385</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.284914</td>\n",
       "      <td>0.403245</td>\n",
       "      <td>0.539258</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               count         mean          std          min          25%  \\\n",
       "index          144.0   261.048611   136.830267     1.000000   144.750000   \n",
       "X              144.0   449.375000   263.691435     0.000000   242.500000   \n",
       "Y              144.0   542.979167   289.228936    19.000000   300.000000   \n",
       "Facies         144.0     0.659722     0.475456     0.000000     0.000000   \n",
       "Porosity       144.0     0.190700     0.031972     0.131230     0.166621   \n",
       "Perm           144.0   510.036736  1136.459068     0.039555     6.950509   \n",
       "AI             144.0  3746.825725   793.196589  1961.600397  3167.631744   \n",
       "Norm_Porosity  144.0     0.475986     0.255894     0.000000     0.283258   \n",
       "Norm_AI        144.0     0.421743     0.187385     0.000000     0.284914   \n",
       "\n",
       "                       50%          75%          max  \n",
       "index           270.000000   381.250000   478.000000  \n",
       "X               400.000000   650.000000   980.000000  \n",
       "Y               579.000000   800.000000   979.000000  \n",
       "Facies            1.000000     1.000000     1.000000  \n",
       "Porosity          0.188733     0.217234     0.256172  \n",
       "Perm             56.886770   356.658709  7452.343369  \n",
       "AI             3668.526774  4244.264532  6194.573653  \n",
       "Norm_Porosity     0.460240     0.688350     1.000000  \n",
       "Norm_AI           0.403245     0.539258     1.000000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's extract the porosity and acoustic impedance features and then look at the resulting DataFrame to ensure that we loaded and reformatted as expected. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Porosity</th>\n",
       "      <th>AI</th>\n",
       "      <th>Norm_Porosity</th>\n",
       "      <th>Norm_AI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.139637</td>\n",
       "      <td>4747.274043</td>\n",
       "      <td>0.067289</td>\n",
       "      <td>0.658089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.170732</td>\n",
       "      <td>4535.625583</td>\n",
       "      <td>0.316164</td>\n",
       "      <td>0.608089</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.244345</td>\n",
       "      <td>2696.102930</td>\n",
       "      <td>0.905345</td>\n",
       "      <td>0.173519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.167125</td>\n",
       "      <td>5500.997419</td>\n",
       "      <td>0.287294</td>\n",
       "      <td>0.836149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.216253</td>\n",
       "      <td>3959.934912</td>\n",
       "      <td>0.680501</td>\n",
       "      <td>0.472088</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Porosity           AI  Norm_Porosity   Norm_AI\n",
       "0  0.139637  4747.274043       0.067289  0.658089\n",
       "1  0.170732  4535.625583       0.316164  0.608089\n",
       "2  0.244345  2696.102930       0.905345  0.173519\n",
       "3  0.167125  5500.997419       0.287294  0.836149\n",
       "4  0.216253  3959.934912       0.680501  0.472088"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_subset = df.iloc[:,[4,6,7,8]]              # extract Porosity and AI for a simple 2D example\n",
    "df_subset.head()                          # preview the new DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Some Parameters\n",
    "\n",
    "From the summary statistics we can assign a reasonable minimum and maximum for each feature.  \n",
    "\n",
    "* We will use this for plotting.\n",
    "\n",
    "We will also set the random number seed to ensure that the program does the same thing everytime it is run.\n",
    "\n",
    "* Change the seed number for a different result\n",
    "\n",
    "We will set the number of prototypes / clusters, *K*\n",
    "\n",
    "We define a dictionary with the color code for each cluster, $k = 1,\\ldots,K$.  Given 7 codes currently, there will be an error if $K$ is set larger than 7.  Add more color codes to the dictionary to allow for mor categories."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "por_min = 0.12; por_max = 0.28\n",
    "AI_min = 1500; AI_max = 6500\n",
    "np.random.seed(210)\n",
    "K = 7                                     # number of prototypes\n",
    "colmap = {1: 'r', 2: 'g', 3: 'b', 4: 'm', 5: 'c', 6: 'k', 7: 'w'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Visualization of Training Data\n",
    "\n",
    "In this exercise, we want to use K-means clustering provide facies based on acoustic impedance and porosity predictor features. \n",
    "\n",
    "* This allows use to group rock with similar petrophysical and geophysical properties.\n",
    "\n",
    "Let's start by looking at the scatterplot of our training data features, porosity and acoustic impedance.  \n",
    "\n",
    "* We will look at the data in original units and normalized units through this entire exercise."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# scatter plot our training data  \n",
    "plt.subplot(121)\n",
    "plt.scatter(df_subset['Porosity'], df['AI'], c=\"black\", alpha = 0.4, linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Acoustic Impedence vs. Porosity'); plt.xlabel('Porosity (fraction)'); plt.ylabel('Acoustic impedance (kg/m^3 x m/s x 10^3)')\n",
    "plt.xlim(por_min, por_max)\n",
    "plt.ylim(AI_min, AI_max)\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.scatter(df_subset['Norm_Porosity'], df['Norm_AI'], c=\"black\", alpha = 0.4, linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Normalized Acoustic Impedence vs. Porosity'); plt.xlabel('Porosity (normalized)'); plt.ylabel('Acoustic impedance (normalized)')\n",
    "plt.xlim(0.0,1.0)\n",
    "plt.ylim(0.0,1.0)\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=1.0, wspace=0.2, hspace=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Initialize K Prototypes\n",
    "\n",
    "First we will assign K prototypes in the feature space randomly.\n",
    "\n",
    "* for K prototypes assign a random porosity and acoustic impedance\n",
    "\n",
    "* don't worry, these prototypes won't make much sense initially, but they will improve\n",
    "\n",
    "We will do this and then visualize the prototypes as red, green, blue etc. dots."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Assign Initial Prototypes \n",
    "centroids = {}\n",
    "for i in range(K):\n",
    "    norm_por = np.random.random(); por = norm_por * (pormax-pormin) + pormin\n",
    "    norm_AI = np.random.random(); AI = norm_AI * (AImax-AImin) + AImin\n",
    "    centroids[i+1] = [por,AI,norm_por,norm_AI]\n",
    "    \n",
    "plt.subplot(121)                          # plot the training data and K prototypes\n",
    "plt.scatter(df_subset['Porosity'], df['AI'], c=\"black\", alpha = 0.4, linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[0], centroids.get(i)[1], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Acoustic Impedence vs. Porosity with Initial Prototypes'); plt.xlabel('Porosity (fraction)'); plt.ylabel('Acoustic impedance (kg/m^3 x m/s x 10^3)')\n",
    "plt.xlim(por_min, por_max)\n",
    "plt.ylim(AI_min, AI_max)\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=1.0, top=1.0, wspace=0.2, hspace=0.2)\n",
    "\n",
    "plt.subplot(122)                          # plot the training data and K prototypes\n",
    "plt.scatter(df_subset['Norm_Porosity'], df['Norm_AI'], c=\"black\", alpha = 0.4, linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[2], centroids.get(i)[3], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Normalized Acoustic Impedence vs. Porosity with Initial Prototypes'); plt.xlabel('Porosity (normalized)'); plt.ylabel('Acoustic impedance (normalized)')\n",
    "plt.xlim(0, 1)\n",
    "plt.ylim(0, 1)\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=1.0, wspace=0.2, hspace=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Assignment of Training Data\n",
    "\n",
    "All training data are assigned to the nearest prototype.  \n",
    "\n",
    "* recall we have a function to do this\n",
    "\n",
    "```python\n",
    "df = assignment(df, centroids) \n",
    "```\n",
    "\n",
    "* we work with the normalized features and visualize normalized and original features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = assignment(df, centroids)            # assign training data to the nearest prototype\n",
    "\n",
    "plt.subplot(121)                          # plot the assigned training data and K prototypes\n",
    "plt.scatter(df['Porosity'], df['AI'], color=df['color'], alpha=0.5, edgecolor='k')\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[0], centroids.get(i)[1], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Acoustic Impedence vs. Porosity with Initial Prototypes'); plt.xlabel('Porosity (fraction)'); plt.ylabel('Acoustic impedance (kg/m^3 x m/s x 10^3)')\n",
    "plt.xlim(por_min, por_max)\n",
    "plt.ylim(AI_min, AI_max)\n",
    "\n",
    "plt.subplot(122)                          # plot the training data and K prototypes\n",
    "plt.scatter(df_subset['Norm_Porosity'], df['Norm_AI'], c=df['color'], alpha = 0.4, linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[2], centroids.get(i)[3], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Normalized Acoustic Impedence vs. Porosity with Initial Prototypes'); plt.xlabel('Porosity (normalized)'); plt.ylabel('Acoustic impedance (normalized)')\n",
    "plt.xlim(0, 1)\n",
    "plt.ylim(0, 1)\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=1.0, wspace=0.2, hspace=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Update the Prototypes\n",
    "\n",
    "Now we reassign the prototypes to the centroids of the training data belonging to each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "old_centroids = copy.deepcopy(centroids)\n",
    "centroids = update(centroids,pormin,pormax,AImin,AImax)\n",
    "    \n",
    "plt.subplot(121)                          # plot the assigned training data and K prototypes\n",
    "ax = plt.gca()\n",
    "plt.scatter(df['Porosity'], df['AI'], color=df['color'], alpha=0.5, edgecolor='k')\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[0], centroids.get(i)[1], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Acoustic Impedence vs. Porosity with Updated Prototypes and Vectors'); plt.xlabel('Porosity (fraction)'); plt.ylabel('Acoustic impedance (kg/m^3 x m/s x 10^3)')\n",
    "plt.xlim(por_min, por_max)\n",
    "plt.ylim(AI_min, AI_max)\n",
    "\n",
    "for i in old_centroids.keys():\n",
    "    old_x = old_centroids[i][0]\n",
    "    old_y = old_centroids[i][1]\n",
    "    dx = (centroids[i][0] - old_centroids[i][0]) \n",
    "    dy = (centroids[i][1] - old_centroids[i][1]) \n",
    "    ax.arrow(old_x, old_y, dx, dy,fc=colmap[i], ec=colmap[i])\n",
    "    \n",
    "plt.subplot(122)                          # plot the assigned training data and K prototypes\n",
    "ax = plt.gca()\n",
    "plt.scatter(df['Norm_Porosity'], df['Norm_AI'], color=df['color'], alpha=0.5, edgecolor='k')\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[2], centroids.get(i)[3], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Normalized Acoustic Impedence vs. Porosity with Updated Prototypes and Vectors'); plt.xlabel('Porosity (normalized)'); plt.ylabel('Acoustic impedance (normalized)')\n",
    "plt.xlim(0, 1)\n",
    "plt.ylim(0, 1)\n",
    "\n",
    "for i in old_centroids.keys():\n",
    "    old_x = old_centroids[i][2]\n",
    "    old_y = old_centroids[i][3]\n",
    "    dx = (centroids[i][2] - old_centroids[i][2]) \n",
    "    dy = (centroids[i][3] - old_centroids[i][3]) \n",
    "    ax.arrow(old_x, old_y, dx, dy,fc=colmap[i], ec=colmap[i])\n",
    "      \n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=1.0, wspace=0.2, hspace=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Repeat the Assignment of the Training Data\n",
    "\n",
    "Once again we assign the training data to the nearest prototype. \n",
    "\n",
    "* Note the prototypes were updated in the previous step so the assignments may change"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = assignment(df, centroids)\n",
    "\n",
    "plt.subplot(121)                          # plot the assigned training data and K prototypes\n",
    "plt.scatter(df['Porosity'], df['AI'], color=df['color'], alpha=0.5, edgecolor='k')\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[0], centroids.get(i)[1], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Acoustic Impedence vs. Porosity with Updated Training Data'); plt.xlabel('Porosity (fraction)'); plt.ylabel('Acoustic impedance (kg/m^3 x m/s x 10^3)')\n",
    "plt.xlim(por_min, por_max)\n",
    "plt.ylim(AI_min, AI_max)\n",
    "\n",
    "plt.subplot(122)                          # plot the training data and K prototypes\n",
    "plt.scatter(df_subset['Norm_Porosity'], df['Norm_AI'], c=df['color'], alpha = 0.4, linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[2], centroids.get(i)[3], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Normalized Acoustic Impedence vs. Porosity with Updated Training Data'); plt.xlabel('Porosity (normalized)'); plt.ylabel('Acoustic impedance (normalized)')\n",
    "plt.xlim(0, 1)\n",
    "plt.ylim(0, 1)\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=1.0, wspace=0.2, hspace=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Iterate Until Convergence \n",
    "\n",
    "Now we interate over the the previous set of steps:\n",
    "\n",
    "* assign the training data to the nearest prototype\n",
    "\n",
    "* update the prototypes \n",
    "\n",
    "We do this until there is no further chance in the category assigned to each of the training data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Continue until all assigned categories don't change any more (code modified from Ben Keen, http://benalexkeen.com/k-means-clustering-in-python/)\n",
    "\n",
    "while True:\n",
    "    closest_centroids = df['closest'].copy(deep=True)\n",
    "    centroids = update(centroids,pormin,pormax,AImin,AImax)\n",
    "    df = assignment(df, centroids)\n",
    "    if closest_centroids.equals(df['closest']):\n",
    "        break\n",
    "\n",
    "plt.subplot(121)                          # plot the assigned training data and K prototypes\n",
    "plt.scatter(df['Porosity'], df['AI'], color=df['color'], alpha=0.5, edgecolor='k')\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[0], centroids.get(i)[1], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Acoustic Impedence vs. Porosity with Final Prototypes'); plt.xlabel('Porosity (fraction)'); plt.ylabel('Acoustic impedance (kg/m^3 x m/s x 10^3)')\n",
    "plt.xlim(por_min, por_max)\n",
    "plt.ylim(AI_min, AI_max)\n",
    "\n",
    "plt.subplot(122)                          # plot the training data and K prototypes\n",
    "plt.scatter(df_subset['Norm_Porosity'], df['Norm_AI'], c=df['color'], alpha = 0.4, linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "for i in centroids.keys():\n",
    "    plt.scatter(centroids.get(i)[2], centroids.get(i)[3], color=colmap[i],linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.title('Normalized Acoustic Impedence vs. Porosity with Final Prototypes'); plt.xlabel('Porosity (normalized)'); plt.ylabel('Acoustic impedance (normalized)')\n",
    "plt.xlim(0, 1)\n",
    "plt.ylim(0, 1)\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=1.0, wspace=0.2, hspace=0.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have demonstrated k-means clustering by-hand, let's try out the scikit-learn implimentation.\n",
    "\n",
    "* we have the typical instantiate, fit and predict steps.  In this case we will stop with fit and use the claster labels assigned at the sample data locations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Porosity</th>\n",
       "      <th>AI</th>\n",
       "      <th>Norm_Porosity</th>\n",
       "      <th>Norm_AI</th>\n",
       "      <th>clusters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.139637</td>\n",
       "      <td>4747.274043</td>\n",
       "      <td>0.067289</td>\n",
       "      <td>0.658089</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.170732</td>\n",
       "      <td>4535.625583</td>\n",
       "      <td>0.316164</td>\n",
       "      <td>0.608089</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.244345</td>\n",
       "      <td>2696.102930</td>\n",
       "      <td>0.905345</td>\n",
       "      <td>0.173519</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.167125</td>\n",
       "      <td>5500.997419</td>\n",
       "      <td>0.287294</td>\n",
       "      <td>0.836149</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.216253</td>\n",
       "      <td>3959.934912</td>\n",
       "      <td>0.680501</td>\n",
       "      <td>0.472088</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Porosity           AI  Norm_Porosity   Norm_AI  clusters\n",
       "0  0.139637  4747.274043       0.067289  0.658089         2\n",
       "1  0.170732  4535.625583       0.316164  0.608089         2\n",
       "2  0.244345  2696.102930       0.905345  0.173519         0\n",
       "3  0.167125  5500.997419       0.287294  0.836149         2\n",
       "4  0.216253  3959.934912       0.680501  0.472088         0"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import warnings                                        # muted warnings due to the updating of a sliced DataFrame\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from sklearn.cluster import KMeans                      # import the KMeans method from scikit-learn\n",
    "n_init = 10                                             # number of random initial centroids (best solution is picked)\n",
    "max_iter = 1000                                         # maximum number of interations to converge\n",
    "seed = 73075                                            # random number seed\n",
    "tol = 1e-6                                              # tolerance to determine solution has convereged\n",
    "kmeans_clustering = KMeans(n_clusters=3, random_state = seed, n_init = n_init, max_iter = max_iter, tol = tol)\n",
    "df_subset['clusters'] = kmeans_clustering.fit(df_subset[['Norm_Porosity','Norm_AI']]).labels_\n",
    "df_subset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
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   ],
   "source": [
    "plt.subplot(111)                          # plot the training data and K prototypes\n",
    "plt.scatter(df_subset['Norm_Porosity'], df_subset['Norm_AI'], c=df_subset['clusters'], alpha = 0.4, linewidths=1.0, verts=None, edgecolors=\"black\")\n",
    "plt.scatter(kmeans_clustering.cluster_centers_[:,0],kmeans_clustering.cluster_centers_[:,1], marker='x', c=['black'])\n",
    "plt.title('Normalized Acoustic Impedence vs. Porosity with Final Prototypes'); plt.xlabel('Porosity (normalized)'); plt.ylabel('Acoustic impedance (normalized)')\n",
    "plt.xlim(0, 1)\n",
    "plt.ylim(0, 1)\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=0.95, top=1.0, wspace=0.2, hspace=0.2)"
   ]
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    "#### Comments\n",
    "\n",
    "There are so many more tests that one could attempt to gain experience with K-means clustering. I'll end here for brevity, but I invite you to continue. Consider, on your own:\n",
    "\n",
    "* change the number of $K$ prototypes\n",
    "\n",
    "* apply the original data (no normalization)\n",
    "\n",
    "* apply other data sets \n",
    "\n",
    "* attempting methods with supervised K-means classification.  \n",
    "\n",
    "I hope you found this tutorial useful. I'm always happy to discuss data analytics, geostatistics, statistical modeling, uncertainty modeling and machine learning,\n",
    "\n",
    "I have other demonstrations on the basics of working with DataFrames, ndarrays, univariate statistics, plotting data, declustering, data transformations, trend modeling and many other workflows available at https://github.com/GeostatsGuy/PythonNumericalDemos and https://github.com/GeostatsGuy/GeostatsPy. \n",
    "  \n",
    "I hope this was helpful,\n",
    "\n",
    "*Michael*\n",
    "\n",
    "#### The Author:\n",
    "\n",
    "### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "*Novel Data Analytics, Geostatistics and Machine Learning Subsurface Solutions*\n",
    "\n",
    "With over 17 years of experience in subsurface consulting, research and development, Michael has returned to academia driven by his passion for teaching and enthusiasm for enhancing engineers' and geoscientists' impact in subsurface resource development. \n",
    "\n",
    "For more about Michael check out these links:\n",
    "\n",
    "#### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n",
    "\n",
    "#### Want to Work Together?\n",
    "\n",
    "I hope this content is helpful to those that want to learn more about subsurface modeling, data analytics and machine learning. Students and working professionals are welcome to participate.\n",
    "\n",
    "* Want to invite me to visit your company for training, mentoring, project review, workflow design and / or consulting? I'd be happy to drop by and work with you! \n",
    "\n",
    "* Interested in partnering, supporting my graduate student research or my Subsurface Data Analytics and Machine Learning consortium (co-PIs including Profs. Foster, Torres-Verdin and van Oort)? My research combines data analytics, stochastic modeling and machine learning theory with practice to develop novel methods and workflows to add value. We are solving challenging subsurface problems!\n",
    "\n",
    "* I can be reached at mpyrcz@austin.utexas.edu.\n",
    "\n",
    "I'm always happy to discuss,\n",
    "\n",
    "*Michael*\n",
    "\n",
    "Michael Pyrcz, Ph.D., P.Eng. Associate Professor The Hildebrand Department of Petroleum and Geosystems Engineering, Bureau of Economic Geology, The Jackson School of Geosciences, The University of Texas at Austin\n",
    "\n",
    "I have other demonstrations on the basics of working with DataFrames, ndarrays, univariate statistics, plotting data, declustering, data transformations, trend modeling and many other workflows available at https://github.com/GeostatsGuy/PythonNumericalDemos and https://github.com/GeostatsGuy/GeostatsPy. \n",
    "  \n",
    "I hope this was helpful,\n",
    "\n",
    "*Michael*\n",
    "\n",
    "Michael Pyrcz, Ph.D., P.Eng. Associate Professor The Hildebrand Department of Petroleum and Geosystems Engineering, Bureau of Economic Geology, The Jackson School of Geosciences, The University of Texas at Austin\n",
    "\n",
    "#### More Resources Available at: [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n"
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